This diploma thesis deals with trading in the international stock markets in conditions of financial crisis. The theoretical part covers basic definitions associated with stock markets, followed by a chapter dedicated to business cycles, which are significantly related to the stock markets. The first goal of the thesis is numerical comparison of the extensions of the actual financial crisis with the most meaningful financial crisis over last one hundred years. The second aim of the work is to effectuate the technical analysis using selected technical indicators and evaluate its results in chosen periods.

The diploma thesis deals with currency market analysis. There are three main types of analysis: fundamental, technical and psychological analysis. Each of these methods contains explanation of logic, on which the method is based, its advantages, disadvantages and specific examples of this analysis. Neural networks are furher explained in technical analysis. The practical part of the diploma thesis builds on knowledge of technical analysis and tests functionality of the neural networks in the environment of currency markets. The model is calibrated first and then it is used to predict the development of major currency pairs. The prediction is carried out on a monthly chart for December 2013.

This diploma thesis describes issues of use of means of artificial intelligence for the decision making support on stock market. It includes theoretical knowledge of technical, fundamental and psychological analysis and artificial intelligence. Based on these facts have been created specific suggestions for the use of artificial neural networks to forecast the future value of the index S&P 500 by using development environment of the MATLAB software.